Geo-location Custom Indexes for Efficient Spatial Queries
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Solution Overview
Problem
Existing systems for computing devices face inefficiencies in storing and processing location information using multiple coordinates (latitude, longitude, elevation) for geo-locations, leading to data storage challenges and computation-intensive operations when determining distances between locations.
Innovation Solution
The implementation of custom indexes for geo-locations using spatial area subdivisions, such as quadtrees and octrees, which divide space into hierarchical cells, allowing for efficient representation and querying of location data without the need for multiple coordinate systems, reducing data storage and computation requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple coordinates (latitude, longitude, elevation) are used to store location information, then location precision is improved, but data storage requirements and computation complexity increase
Solution Approach 1:
The patent divides the geographic space into hierarchical cells (quadtree/octree structure) where each cell is represented by a single index value. This segmentation transforms the problem of storing multiple coordinates into storing simple cell indices, reducing both data storage requirements and computation complexity while maintaining location precision through the hierarchical cell structure.
Solution Approach 2:
The patent introduces cell index values as an intermediary representation between the actual geographic coordinates and the query system. Instead of directly storing and processing multiple coordinates, the system uses these intermediary index values to represent locations, significantly simplifying storage and computation while preserving the ability to determine distances and perform queries.
2Measurement precision
If multiple coordinates are stored for each geo-location, then location accuracy is improved, but data storage space increases
Solution Approach 1:
The patent segments the geographic space into hierarchical cells and represents each cell by a single index value. This segmentation reduces the amount of data needed to store location information from multiple coordinates to a compact cell index, while the hierarchical structure maintains location accuracy by allowing navigation through the cell tree to achieve desired precision.
Solution Approach 2:
The patent creates a simplified copy of location data using cell index values instead of original coordinate data. These index values are compact representations that can be stored efficiently and used for queries, while the full coordinate information is only retrieved when needed through the hierarchical cell structure.
3Measurement precision
If multiple coordinates are used to represent locations, then spatial representation accuracy is improved, but query processing time increases
Solution Approach 1:
The patent segments space into hierarchical cells with index values that can be quickly compared and filtered. This segmentation enables efficient query processing by navigating the cell hierarchy and comparing index values rather than performing complex distance calculations with multiple coordinates, significantly improving query processing speed while maintaining spatial representation accuracy.
Solution Approach 2:
The patent performs preliminary organization of geographic data into a hierarchical cell structure with index values before queries are executed. This preliminary action creates an optimized data structure that enables fast query processing through index-based navigation and filtering, avoiding the need for complex real-time coordinate calculations during query execution.
Data Source
AI summary
Apparatuses, systems, and methods for generating and utilizing custom indexes for a plurality of geo-locations are described. A plurality of indexes are generated, each corresponding to one of a plurality of geo-locations, based on spatial area subdivisions of a space including the plurality of geo-locations. A points of interest (POIs) query is received, wherein results of the query are to be limited by a distance value. One or more geo-locations are identified as POIs within the distance value from a first geo-location of the plurality of geo-locations based on the corresponding indexes of the one or more identified geo-locations.